Can I remove a participant from a live session through the agent?

Yes. The `remove_peer` tool allows your AI agent to disconnect any participant from an active session using their peer ID. You can also provide a custom reason for the removal, which will be logged in your session history.

How do I check if a video room is currently active?

Use the `list_sessions` tool and filter by the specific room ID and status 'active'. Your agent will return any ongoing sessions for that room along with the number of participants currently joined.

Can I see all cloud recordings for a specific room?

Absolutely. Use the `list_recordings` tool and provide the room ID. Your agent will retrieve all recordings associated with that room, showing their status and technical metadata for auditing purposes.

100ms MCP Server for CrewAI 9 tools — connect in under 2 minutes

Name: 100ms
Availability: InStock
Author: Vinkius

docs.crewai.com/mcp/overview

Built by Vinkius GDPR 9 Tools Framework

Connect your CrewAI agents to 100ms through Vinkius, pass the Edge URL in the `mcps` parameter and every 100ms tool is auto-discovered at runtime. No credentials to manage, no infrastructure to maintain.

Get MCP Server for AI Agents

ASK AI ABOUT THIS MCP SERVER

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Vinkius supports streamable HTTP and SSE.

python

from crewai import Agent, Task, Crew

agent = Agent(
    role="100ms Specialist",
    goal="Help users interact with 100ms effectively",
    backstory=(
        "You are an expert at leveraging 100ms tools "
        "for automation and data analysis."
    ),
    # Your Vinkius token. get it at cloud.vinkius.com
    mcps=["https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"],
)

task = Task(
    description=(
        "Explore all available tools in 100ms "
        "and summarize their capabilities."
    ),
    agent=agent,
    expected_output=(
        "A detailed summary of 9 available tools "
        "and what they can do."
    ),
)

crew = Crew(agents=[agent], tasks=[task])
result = crew.kickoff()
print(result)

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Ed25519Audit chain

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Stream every event to Splunk, Datadog, or your own webhook in real-time

* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure

About 100ms MCP Server

Connect your 100ms account to any AI agent and manage your live video infrastructure through natural conversation.

When paired with CrewAI, 100ms becomes a first-class tool in your multi-agent workflows. Each agent in the crew can call 100ms tools autonomously, one agent queries data, another analyzes results, a third compiles reports, all orchestrated through Vinkius with zero configuration overhead.

What you can do

Room Management — List all virtual rooms, retrieve deep technical metadata, and create new rooms with specific templates and descriptions
Session Monitoring — Monitor active or completed video sessions in real-time and retrieve session history across your organization
Participant Governance — List all peers (participants) currently in a session and retrieve their unique IDs and roles
Peer Control — Remotely remove or kick participants from active sessions with custom reasons directly from your agent
Recording Discovery — List and browse cloud recordings, filtered by room or status (completed, failed, or processing)
Operational Insights — Quickly find unique room, session, and peer IDs required for automated video workflows
Scalable Infrastructure — Verify your live video configurations and template settings through automated metadata retrieval

The 100ms MCP Server exposes 9 tools through the Vinkius. Connect it to CrewAI in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

How to Connect 100ms to CrewAI via MCP

Follow these steps to integrate the 100ms MCP Server with CrewAI.

Install CrewAI

Run pip install crewai

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token from cloud.vinkius.com

Customize the agent

Adjust the role, goal, and backstory to fit your use case

Run the crew

Run python crew.py. CrewAI auto-discovers 9 tools from 100ms

Why Use CrewAI with the 100ms MCP Server

CrewAI Multi-Agent Orchestration Framework provides unique advantages when paired with 100ms through the Model Context Protocol.

Multi-agent collaboration lets you decompose complex workflows into specialized roles, one agent researches, another analyzes, a third generates reports, each with access to MCP tools

CrewAI's native MCP integration requires zero adapter code: pass Vinkius Edge URL directly in the `mcps` parameter and agents auto-discover every available tool at runtime

Built-in task delegation and shared memory mean agents can pass context between steps without manual state management, enabling multi-hop reasoning across tool calls

Sequential and hierarchical crew patterns map naturally to real-world workflows: enumerate subdomains → analyze DNS history → check WHOIS records → compile findings into actionable reports

100ms + CrewAI Use Cases

Practical scenarios where CrewAI combined with the 100ms MCP Server delivers measurable value.

Automated multi-step research: a reconnaissance agent queries 100ms for raw data, then a second analyst agent cross-references findings and flags anomalies. all without human handoff

Scheduled intelligence reports: set up a crew that periodically queries 100ms, analyzes trends over time, and generates executive briefings in markdown or PDF format

Multi-source enrichment pipelines: chain 100ms tools with other MCP servers in the same crew, letting agents correlate data across multiple providers in a single workflow

Compliance and audit automation: a compliance agent queries 100ms against predefined policy rules, generates deviation reports, and routes findings to the appropriate team

100ms MCP Tools for CrewAI (9)

These 9 tools become available when you connect 100ms to CrewAI via MCP:

create_room

Use this when the user asks to start or host a new meeting space. Create a new video room

get_room

Requires the unique room ID. Get the configuration and details of a specific video room

get_session

Get the details and metadata of a specific video session

list_peers

Requires the session ID. List all participants currently inside an active video session

list_recordings

Can optionally filter by room ID or the status of the recording. List cloud recordings of video rooms

list_rooms

Use this to find a room ID. List all video rooms in the 100ms account

list_sessions

You can filter by room ID or status. Use this to find who attended past meetings. List active or past video sessions

remove_peer

Requires the session ID and the peer ID. Kick or remove a specific participant from an active video session

update_room

Requires the room ID. Update the settings of an existing video room

Example Prompts for 100ms in CrewAI

Ready-to-use prompts you can give your CrewAI agent to start working with 100ms immediately.

"List all my video rooms in 100ms."

"Are there any active sessions for the 'Town Hall' room right now?"

"Remove participant 'peer-123' from the session 'sess-abc' for 'violating community guidelines'."

Troubleshooting 100ms MCP Server with CrewAI

Common issues when connecting 100ms to CrewAI through the Vinkius, and how to resolve them.

MCP tools not discovered

Ensure the Edge URL is correct. CrewAI connects lazily when the crew starts. check console output.

Agent not using tools

Make the task description specific. Instead of "do something", say "Use the available tools to list contacts".

Timeout errors

CrewAI has a 10s connection timeout by default. Ensure your network can reach the Edge URL.

Rate limiting or 429 errors

Vinkius enforces per-token rate limits. Check your subscription tier and request quota in the dashboard. Upgrade if you need higher throughput.

100ms + CrewAI FAQ

Common questions about integrating 100ms MCP Server with CrewAI.

How does CrewAI discover and connect to MCP tools?

CrewAI connects to MCP servers lazily. when the crew starts, each agent resolves its MCP URLs and fetches the tool catalog via the standard tools/list method. This means tools are always fresh and reflect the server's current capabilities. No tool schemas need to be hardcoded.

Can different agents in the same crew use different MCP servers?

Yes. Each agent has its own mcps list, so you can assign specific servers to specific roles. For example, a reconnaissance agent might use a domain intelligence server while an analysis agent uses a vulnerability database server.

What happens when an MCP tool call fails during a crew run?

CrewAI wraps tool failures as context for the agent. The LLM receives the error message and can decide to retry with different parameters, fall back to a different tool, or mark the task as partially complete. This resilience is critical for production workflows.

Can CrewAI agents call multiple MCP tools in parallel?

CrewAI agents execute tool calls sequentially within a single reasoning step. However, you can run multiple agents in parallel using process=Process.parallel, each calling different MCP tools concurrently. This is ideal for workflows where separate data sources need to be queried simultaneously.

Can I run CrewAI crews on a schedule (cron)?

Yes. CrewAI crews are standard Python scripts, so you can invoke them via cron, Airflow, Celery, or any task scheduler. The crew.kickoff() method runs synchronously by default, making it straightforward to integrate into existing pipelines.